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Brychta, Jiří, and Miloslav Janeček. "Determination of erosion rainfall criteria based on natural rainfall measurement and its impact on spatial distribution of rainfall erosivity in the Czech Republic." Soil and Water Research 14, No. 3 (May 27, 2019): 153–62. http://dx.doi.org/10.17221/91/2018-swr.
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Rainfall erosivity is the main factor of the USLE or RUSLE equations. Its accuracy depends on recording precision and its temporal resolution, number of stations and their spatial distribution, length of recorded period, recorded period, erosion rainfall criteria, time step of rainfall intensity and interpolation method. This research focuses on erosion rainfall criteria. A network of 32 ombrographic stations, 1-min temporal resolution rainfall data, 35.6-year period and experimental runoff plots were used. We analysed 8951 rainfalls from ombrographic stations, 100 rainfalls and caused soil losses and runoffs from experimental runoff plots. Main parameter which influenced the number of erosion rainfalls was the precondition AND/OR which determines if conditions of rainfall total (H) have to be fulfilled simultaneously with rainfall intensity (I<sub>15</sub> or I<sub>30</sub>) or not. We proved that if parameters I<sub>15 </sub>> 6.25 mm/15 min AND H > 12.5 mm were fulfilled, then 84.2% of rainfalls caused soil loss > 0.5 t/ha and 73.7% ≥ 1 t/ha. In the case of precondition OR only 44.6% of rainfalls caused soil loss > 0.5 t/ha and 33.9% ≥ 1 t/ha. If the precondition AND was fulfilled, there were on average 75.5 rainfalls, average R factor for each rainfall was 21 MJ/ha·cm/h (without units below in the text, according international unit: 210 MJ/ha·mm/h) and average annual R factor was 45.4. In the case of precondition OR there were on average 279 rainfalls but average R factor for each rainfall was only 9.1 and average annual R factor was 67.4. Therefore if the precondition OR is used, R factor values are overestimated due to a high number of rainfalls with no or very low erosive potential. The resulting overestimated soil losses calculated using USLE/RUSLE subsequently cause an overestimation of financial expenses for erosion-control measures.
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Fatawa, Muhammad Ihsan, Edi Santosa, Dhika Prita Hapsari, and Krisantini. "Climate change and its adaptation strategies on tea plantation in West Java, Indonesia." Indonesian Journal of Agronomy 51, no. 2 (August 25, 2023): 257–68. http://dx.doi.org/10.24831/ija.v51i2.47081.
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Climate change, i.e., changing rainfall refers to drought and excess rainfall, is known to affect the growth and yield of tea production in many regions. However, research on the impact of climate change on tea plantations in Indonesia is still limited. The study aimed to evaluate the impact of changing rainfall on the productivity of tea plantation at Cianjur, West Java. The data was collected from interviews, field data, and company records from April to July 2022. The results showed that changing rainfall of both limited rainfalls during El Nino and excess rainfall during La Nina affected the tea production. Annual tea productivity declined during both climatic events. Shortage of water during El Nino primarily reduced crop growth, while excess rainfall during La Nina reduced the capacity of tea pickers and increased labor for crop maintenance. Failure to adapt to the direct and indirect impacts of climate change could contribute to declining tea production in Indonesia. Thus, comprehensive action is needed including capacity building in human resources, water management, and microclimate adaptation such as shading plants and tolerant clones to sustain tea production under climate change events.
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Minea, Gabriel, and Gabriela Ioana-Toroimac. "Land use impact on overland flow: micro-scale field experimental analysis." Journal of Water and Land Development 29, no. 1 (June 1, 2016): 67–74. http://dx.doi.org/10.1515/jwld-2016-0013.
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Abstract The objective of this paper was to experimentally investigate the hydrological effect of land use on overland flow at micro-scale. The research was based on field experiments made with stationary and expeditionary measurements on runoff plots. Plots are located in the Curvature Subcarpathians, form part of the Aldeni Experimental Basin (Romania) and cover an area of 80 m2. The land is covered with perennial grass and bare soil. The experiments in this field were performed under natural and simulated rainfalls. The plots data (rainfall and discharges) obtained during the experiments conducted in the warm semester (IV–IX) and one artificial rainfall (1 mm·min−1) were used. Significant variations in hydrological responses to rainfall rates were identified for the two land uses. On average, overland flow parameters on runoff plots covered with grasses were reduced to maximum 28% for discharges and to 50% for volumes while in the case of simulated rainfalls, the runoff rates were significantly increased on the bare soil plot. Grasses have a very important function as they cover and protect the soil and slow down the overland flow.
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SEETHARAM, K. "Impact of Madden-Julian oscillations on the Indian summer monsoon sub-divisional rainfalls." MAUSAM 59, no. 2 (November 27, 2021): 195–210. http://dx.doi.org/10.54302/mausam.v59i2.1251.
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Indian summer monsoon rainfall exhibits inter-seasonal variations in the time scales of 2-7 years which are linked to quasi-biennial oscillations and El nino-Southern Oscillation phenomenon and also intra-seasonal variations in the time-scale of 30-60 days which are linked to activity of MJO which emerged as a dominant mode of intra-seasonal oscillations of Indian summer monsoon rainfall in addition to the other modes of low frequency oscillations. In this scenario, the inter and intra seasonal variability of 29 meteorological sub-divisional rainfalls has been investigated by correlating the MJO indices at 10 different longitudes covering Indian, Pacific and Atlantic Oceans with cumulative sub-divisional summer monsoon rainfall (1979 – 2000). The results were discussed.
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Vilayvong, K., N. Yasufuku, and R. Ishikura. "Evaluation of rainfall erosivity and impact forces using strain gauges." Lowland Technology International 17, no. 4 (2016): 207–17. http://dx.doi.org/10.14247/lti.17.4_207.
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Tunas, I. G., H. Azikin, and G. M. Oka. "Impact of Extreme Rainfall on Flood Hydrographs." IOP Conference Series: Earth and Environmental Science 884, no. 1 (November 1, 2021): 012018. http://dx.doi.org/10.1088/1755-1315/884/1/012018.
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Abstract Extreme rainfall is the main factor triggering flooding in various regions of the world including Indonesia. The increase in intensity and duration of current extreme rainfall is predicted as a result of global climate change. This paper aims to analyze the impact of extreme rainfall to the peak discharge of flood hydrographs at a watershed outlet in Palu, Sulawesi, Indonesia. Maximum daily rainfall data for the period 1990-1999 recorded at the Palu Meteorological Station, Central Sulawesi were selected using the Annual Maximum Series Method, and grouped into two types. Type I is the maximum daily rainfall data with extreme events and Type II is the maximum daily rainfall data without extreme events. Frequency analysis was applied to the two data groups using the best distribution method of: Normal, Normal Log, Pearson III Log, and Gumbel to obtain the design rainfall of each data group. In the next stage, the design rainfall transformation into a flood hydrograph is performed using the Nakayasu Synthetic Unit Hydrograph based on a number of return periods in one of the rivers flowing into Palu Bay, namely the Poboya River. The analysis results show that the design rainfall graphs with both extreme rainfall and without extreme rainfall are identical at the low return period and divergent at the high return period with a difference of up to 21.6% at the 1000-year return period. Correspondingly, extreme rainfall has a greater impact at the peak of the flood hydrograph with increasing return periods ranging from -1.28% to 26.81% over the entire return period.
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Chumchean, Siriluk, Ashish Sharma, and Alan Seed. "Radar rainfall error variance and its impact on radar rainfall calibration." Physics and Chemistry of the Earth, Parts A/B/C 28, no. 1-3 (January 2003): 27–39. http://dx.doi.org/10.1016/s1474-7065(03)00005-6.
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M. R. Savabi and D. E. Stott. "Plant Residue Impact on Rainfall Interception." Transactions of the ASAE 37, no. 4 (1994): 1093–98. http://dx.doi.org/10.13031/2013.28180.
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Yu, Yang, Keisuke Kojima, Kyoungjin An, and Hiroaki Furumai. "Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo." Water Science and Technology 68, no. 3 (August 1, 2013): 544–51. http://dx.doi.org/10.2166/wst.2013.253.
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Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.
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Vemula, Swathi, K. Srinivasa Raju, and S. Sai Veena. "Modelling impact of future climate and land use land cover on flood vulnerability for policy support – Hyderabad, India." Water Policy 22, no. 5 (July 27, 2020): 733–47. http://dx.doi.org/10.2166/wp.2020.106.
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Abstract The study analyses the impact of climate change and land use land cover (LULC) on runoff of Hyderabad city, India for the years 1995, 2005, 2016 and 2031. Flood vulnerability was evaluated for extreme historic and future rainfall events. Maximum daily rainfalls of 132, 181 and 165 mm that occurred in the decades of 1990–2000, 2001–2010 and 2011–2016 were considered for historic rainfall–runoff modelling. Complementarily in climate change, maximum daily rainfall of 266 mm predicted during 2020–2040 by Geophysical Fluid Dynamics Laboratory-Coupled Model 3 (GFDL-CM3) Representative Concentration Pathway (RCP) 2.6, was analysed for rainfall-runoff scenario in 2031. LULC was assessed from historic maps and the master plan of the city. Peak runoff was modelled in Storm Water Management Model (SWMM) for corresponding daily rainfall and LULC. The floodplain of the river Musi was modelled in Hydrological Engineering Center-River Analysis System (HEC-RAS). Results showed that changing rainfall and LULC increased peak runoff by three times, and flood depth in the river increased by 22% from 1995 to 2031. In 2016 and 2031, 48 and 51% of the city was highly vulnerable. Five detention basins were proposed to combat increasing runoff, due to which highly vulnerable areas reduced by 8% in 2016 and 9% in 2031.
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Al Saji, M., J. J. O'Sullivan, and A. O'Connor. "Design impact and significance of non-stationarity of variance in extreme rainfall." Proceedings of the International Association of Hydrological Sciences 371 (June 12, 2015): 117–23. http://dx.doi.org/10.5194/piahs-371-117-2015.
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Abstract. Stationarity in hydro-meteorological records is often investigated through an assessment of the mean value of the tested parameter. This is arguably insufficient for capturing fully the non-stationarity signal, and parameter variance is an equally important indicator. This study applied the Mann-Kendall linear and Mann-Whitney-Wilcoxon step change trend detection techniques to investigate the changes in the mean and variance of annual maximum daily rainfalls at eight stations in Dublin, Ireland, where long and high quality daily rainfall records were available. The eight stations are located in a geographically similar and spatially compact region (< 950 km2) and their rainfalls were shown to be well correlated. Results indicate that while significant positive step changes were observed in mean annual maximum daily rainfalls (1961 and 1997) at only two of the eight stations, a significant and consistent shift in the variance was observed at all eight stations during the 1980's. This period saw a widely noted positive shift in the winter North Atlantic Oscillation that greatly influences rainfall patterns in Northern Europe. Design estimates were obtained from a frequency analysis of annual maximum daily rainfalls (AM series) using the Generalised Extreme Value distribution, identified through application of the Modified Anderson Darling Goodness of Fit criterion. To evaluate the impact of the observed non-stationarity in variance on rainfall design estimates, two sets of depth-frequency relationships at each station for return periods from 5 to 100-years were constructed. The first was constructed with bootstrapped confidence intervals based on the full AM series assuming stationarity and the second was based on a partial AM series commencing in the year that followed the observed shift in variance. Confidence intervals distinguish climate signals from natural variability. Increases in design daily rainfall estimates obtained from the depth-frequency relationship developed from the truncated AM series, as opposed to those using the full series, ranged from 5 to 16% for the 5-year event and from 20 to 41% for the 100-year event. Results indicate that the observed trends exceed the envelopes of natural climate variability and suggest that the non-stationarity in variance is associated with a climate change signal. Results also illustrate the importance of considering trends in higher order moments (e.g. variance) of hydro-meteorological variables in assessing non-stationarity influences.
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Kalaivani, A. S., and M. Ramesh. "Rainfall and Its Impact on Maize Yield." International Review of Business and Economics 1, no. 3 (2018): 104–6. http://dx.doi.org/10.56902/irbe.2018.1.3.30.
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The present study is to analyze the impact of rainfall on maize yield in Cuddalore district based on ten years data (2005-2006 to 2014- 2015). The study conducted with the objective of relationship between area, production, actual rainfall, and maize yield in the study area. The results of the study reveal that actual rainfall adversely affects maize productivity, while the effect of actual rainfall is maximum negative and no significant for maize crops.
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Mondal, M. Shahjahan, Sara Nowreen, and Mostofa Najmus Sakib. "Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model." Climate 8, no. 2 (January 27, 2020): 20. http://dx.doi.org/10.3390/cli8020020.
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The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios.
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Johannsen, Lisbeth Lolk, Nives Zambon, Peter Strauss, Tomas Dostal, Martin Neumann, David Zumr, Thomas A. Cochrane, and Andreas Klik. "Impact of Disdrometer Types on Rainfall Erosivity Estimation." Water 12, no. 4 (March 28, 2020): 963. http://dx.doi.org/10.3390/w12040963.
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Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.
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Lodder, J., M. A. Van Nierop, E. Van Staden, and S. J. Piketh. "Characterising the impact of rainfall on dustfall rates." Clean Air Journal 26, no. 2 (December 3, 2016): 28–33. http://dx.doi.org/10.17159/2410-972x/2016/v26n2a10.
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Soil moisture increased the cohesion potential between particles, reducing the ability of the particle to be entrained. Dust suppression techniques are designed to increase soil moisture and therefore soil cohesion through the application of water or water-based chemicals to surfaces that have known potential for dust entrainment. Rainfall has the ability to act as a natural dust suppression mechanism; however, there is a paucity of literature on the actual effectiveness of rainfall in this regard. The ASTM D1739 methods for dustfall monitoring, commonly used in South Africa, and the National Dust Control Regulations (2013), both state that rainfall should be recorded when conducting dustfall monitoring. The rationale is that rainfall or the absence thereof, results in lower or higher dustfall rates, respectively. A suitable study site was identified in Mpumalanga, South Africa. This site had eight non-directional dustfall samplers in the near vicinity of an air quality monitoring station. Dustfall results from the eight samplers were analysed based on four scenarios, two that considers the presence of rainfall and two that consider the absence of rainfall. This analysis was further combined with wind speed data. This study, over a 24-month period indicates that there is no substantial evidence that above average rainfall will result in below average dustfall. This occurred for one month out of 24 months. Conversely, there is no consensus that the absence of rainfall will result in higher dustfall rates, which occurred cumulatively 30% of the time. Additional environmental and / or operational information may have a greater influence on dustfall compared to rainfall. Careful consideration should be taken to prevent misrepresentation of causational effects of rainfall on dustfall results. Management of dust should be undertaken through dust mitigation measures irrespective of the natural rainfall regime.
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Chen, Jian, Yaowei Li, and Shanju Zhang. "Impact of Different Design Rainfall Pattern Peak Factors on Urban Flooding." Water 15, no. 13 (July 5, 2023): 2468. http://dx.doi.org/10.3390/w15132468.
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In order to investigate the influence of different design rainfall peaks on urban flooding characteristics based on the MIKE hydrodynamic model, the inundation process scenarios were extrapolated for different recurrence periods and three single- and double-peak rainfall types in Zhoukou city as an example, and the equivalent values of total inundation and inundation area were compared and analysed. The results show that bimodal rainfall has a higher risk of inundation than unimodal rainfall for the same rainfall ephemeris and return period. For unimodal rainfall, when the return period is less than 20 years, the more advanced the rainfall peak, the more severe the design rainfall inundation. When the return period is greater than 20 years, the further back the rainfall peak, the more severe the inundation of the design rainfall. The difference between the risk of inundation due to single- and double-peaked rainfall decreases as the return period increases.
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Du, Yu, Ting Xu, Yuzhang Che, Bifeng Yang, Shaojie Chen, Zhikun Su, Lianxia Su, Yangruixue Chen, and Jiafeng Zheng. "Uncertainty Quantification of WRF Model for Rainfall Prediction over the Sichuan Basin, China." Atmosphere 13, no. 5 (May 20, 2022): 838. http://dx.doi.org/10.3390/atmos13050838.
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The mesoscale Weather Research and Forecasting (WRF) model has been widely employed to forecast day-ahead rainfalls. However, the deterministic predictions from the WRF model incorporate relatively large errors due to numerical discretization, inaccuracies in initial/boundary conditions and parameterizations, etc. Among them, the uncertainties in parameterization schemes have a huge impact on the forecasting skill of rainfalls, especially over the Sichuan Basin which is located east of the Tibetan Plateau in southwestern China. To figure out the impact of various parameterization schemes and their interactions on rainfall predictions over the Sichuan Basin, the Global Forecast System data are chosen as the initial/boundary conditions for the WRF model and 48 ensemble tests have been conducted based on different combinations of four microphysical (MP) schemes, four planetary boundary layer (PBL) schemes, and three cumulus (CU) schemes, for four rainfall cases in summer. Compared to the observations obtained from the Chinese ground-based and encrypted stations, it is found that the Goddard MP scheme together with the asymmetric convective model version 2 PBL scheme outperforms other combinations. Next, as the first step to explore further improvement of the WRF physical schemes, the polynomial chaos expansion (PCE) approach is then adopted to quantify the impacts of several empirical parameters with uncertainties in the WRF Single Moment 6-class (WSM6) MP scheme, the Yonsei University (YSU) PBL scheme and the Kain-Fritsch CU scheme on WRF rainfall predictions. The PCE statistics show that the uncertainty of the scaling factor applied to ice fall velocity in the WSM6 scheme and the profile shape exponent in the YSU scheme affects more dominantly the rainfall predictions in comparison with other parameters, which sheds a light on the importance of these schemes for the rainfall predictions over the Sichuan Basin and suggests the next step to further improve the physical schemes.
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Xie, Zongxu, Hanbo Yang, Huafang Lv, and Qingfang Hu. "Seasonal Characteristics of Disdrometer-Observed Raindrop Size Distributions and Their Applications on Radar Calibration and Erosion Mechanism in a Semi-Arid Area of China." Remote Sensing 12, no. 2 (January 12, 2020): 262. http://dx.doi.org/10.3390/rs12020262.
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Raindrop size distributions (DSDs) are the microphysical characteristics of raindrop spectra. Rainfall characterization is important to: (1) provide information on extreme rate, thus, it has an impact on rainfall related hazard; (2) provide data for indirect observation, model and forecast; (3) calibrate and validate the parameters in radar reflectivity-rainfall intensity (Z-R) relationships (quantitative estimate precipitation, QPE) and the mechanism of precipitation erosivity. In this study, the one-year datasets of raindrop spectra were measured by an OTT Parsivel-2 Disdrometer placed in Yulin, Shaanxi Province, China. At the same time, four TE525MM Gauges were also used in the same location to check the disdrometer-measured rainfall data. The theoretical formula of raindrop kinetic energy-rainfall intensity (KE-R) relationships was derived based on the DSDs to characterize the impact of precipitation characteristics and environmental conditions on KE-R relationships in semi-arid areas. In addition, seasonal rainfall intensity curves observed by the disdrometer of the area with application to erosion were characterized and estimated. The results showed that after quality control (QC), the frequencies of raindrop spectra data in different seasons varied, and rainfalls with R within 0.5–5 mm/h accounted for the largest proportion of rainfalls in each season. The parameters in Z-R relationships (Z = aRb) were different for rainfall events of different seasons (a varies from 78.3–119.0, and b from 1.8–2.1), and the calculated KE-R relationships satisfied the form of power function KE = ARm, in which A and m are parameters derived from rainfall shape factor μ. The sensitivity analysis of parameter A with μ demonstrated the applicability of the KE-R formula to different precipitation processes in the Yulin area.
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Wu, Lianhui, Kenji Taniguchi, and Yoshimitsu Tajima. "Impact of Climate Change on Flood Hazard at Airports on Pacific Islands: A Case Study of Faleolo International Airport, Samoa." Journal of Disaster Research 16, no. 3 (April 1, 2021): 351–62. http://dx.doi.org/10.20965/jdr.2021.p0351.
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Climate change is believed to have increased the intensity and frequency of heavy rainfall, and also to have caused sea level rises over this century and beyond. There is widespread concern that small-island nations are particularly vulnerable to increasing risk of inland flood due to such climate change. Understanding the impact of climate change on flood hazard is of great importance for these countries for the development of better protection and adaptation strategies. This study conducted a case study focusing on the impact of climate change on flood hazard at Faleolo International Airport (FIA), Samoa. FIA is a typical small islands airport, located on the lowland along the coast fronted by a fringing reef. Annual maximum daily rainfalls for different return periods were first estimated for the present and future climate around FIA. The estimated rainfalls were input as the forcing of a two-dimensional flood inundation model to investigate the flooding behavior and effectiveness of probable drainage systems. Results showed that a part of the runway can be inundated under heavy rainfall. Construction of drainage pipes significantly contributes to reducing the flood hazard level. Sensitivity analysis showed that the astronomical tide level has relatively little influence on the performance of the drainage system, while the combination of sea level rise and the sea level anomaly induced by stormy waves on the fringing reef could have non-negligible impacts on the drainage system. Location of the drainage pipe is also important to effectively mitigate flooding. The time-concentration of torrential rainfall may also significantly impact the overall performance of the drainage system.
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Charles, Stephen P., Francis H. S. Chiew, Nicholas J. Potter, Hongxing Zheng, Guobin Fu, and Lu Zhang. "Impact of downscaled rainfall biases on projected runoff changes." Hydrology and Earth System Sciences 24, no. 6 (June 8, 2020): 2981–97. http://dx.doi.org/10.5194/hess-24-2981-2020.
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Abstract. Realistic projections of changes to daily rainfall frequency and magnitude, at catchment scales, are required to assess the potential impacts of climate change on regional water supply. We show that quantile–quantile mapping (QQM) bias-corrected daily rainfall from dynamically downscaled WRF simulations of current climate produce biased hydrological simulations, in a case study for the state of Victoria, Australia (237 629 km2). While the QQM bias correction can remove bias in daily rainfall distributions at each 10 km × 10 km grid point across Victoria, the GR4J rainfall–runoff model underestimates runoff when driven with QQM bias-corrected daily rainfall. We compare simulated runoff differences using bias-corrected and empirically scaled rainfall for several key water supply catchments across Victoria and discuss the implications for confidence in the magnitude of projected changes for mid-century. Our results highlight the imperative for methods that can correct for temporal and spatial biases in dynamically downscaled daily rainfall if they are to be suitable for hydrological projection.
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Kleinheinz, Gregory T., Colleen M. McDermott, Sarah Hughes, and Amanda Brown. "Effects of Rainfall onE. coliConcentrations at Door County, Wisconsin Beaches." International Journal of Microbiology 2009 (2009): 1–9. http://dx.doi.org/10.1155/2009/876050.
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Rainfall and its associated storm water runoff have been associated with transport of many pollutants into beach water. Fecal material, from a variety of animals (humans, pets, livestock, and wildlife), can wash into beach water following rainfall and result in microbial contamination of the beach. Many locales around the world issue pre-emptive beach closures associated with rainfall. This study looked at eight beaches located in Door County, Wisconsin, on Lake Michigan to determine the impact of rainfall onE. coliconcentrations in beach water. Water samples were collected from beach water and storm water discharge pipes during rainfall events of 5 mm in the previous 24 hours. Six of the eight beaches showed a significant association between rainfall and elevated beach waterE. coliconcentrations. The duration of the impact of rainfall on beach waterE. coliconcentrations was variable (immediate to 12 hours). Amount of rainfall in the days previous to the sampling did not have significant impact on theE. coliconcentrations measured in beach water. Presence of storm water conveyance pipes adjacent to the beach did not have a uniform impact on beach waterE. coliconcentrations. This study suggests that each beach needs to be examined on its own with regard to rain impacts onE coliconcentrations in beach water.
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Khosh Bin Ghomash, Shahin, Daniel Bachmann, Daniel Caviedes-Voullième, and Christoph Hinz. "Impact of Rainfall Movement on Flash Flood Response: A Synthetic Study of a Semi-Arid Mountainous Catchment." Water 14, no. 12 (June 8, 2022): 1844. http://dx.doi.org/10.3390/w14121844.
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Rainfall is a spatiotemporally varied process and key to accurately capturing catchment runoff and determining flood response. Flash flood response of a catchment can be strongly governed by a rainfall’s spatiotemporal variability and is influenced by storm movement which drives a continuous spatiotemporal change throughout a rainfall event. In this work, the sensitivity of runoff and flooded areas to rainfall movement are assessed in the Kan catchment (Iran). The allochthonous nature of floods in the catchment and how they interact with the effects of rainfall movement are investigated. Fifty synthetic rain hyetographs are generated and traversed over the catchment under different velocities and directions and used to force a 1D/2D hydrodynamic model. The results suggest rainfall movement affects the runoff response in different degrees. Peak discharge, hydrograph shapes and flooded areas are affected. Storms with higher velocities result in higher peaks and faster onsets of runoff and consequently higher flooded areas in comparison to slower storms. The direction of the movement also plays a role. Storms moving along the average direction of the stream result in higher peaks and flooded areas. The relevance of storm direction is greater for slow moving storms. Additionally, the influence of rainfall movement is modulated by hyetograph structure, and the allochthonous behavior is greatly dependent on the location within the drainage network at which it is assessed.
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Vidas, Marijo, Vladan Tubić, Ivan Ivanović, and Marko Subotić. "One Approach to Quantifying Rainfall Impact on the Traffic Flow of a Specific Freeway Segment." Sustainability 14, no. 9 (April 21, 2022): 4985. http://dx.doi.org/10.3390/su14094985.
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Spatial constraints in urban areas very often lead to the application of traffic management measures to meet transport demands. Accordingly, it is very important to identify all potential impacts that could lead to reductions in the street network’s capacity. One such impact is weather conditions. The main motivation of this research is to analyze the impacts of rainfall on one of the most important segments of Belgrade’s street network that represents part of a freeway passing the city center. Our focus is on quantifying the impact of rainfall on speed and capacity. This paper proposes a new approach to analyzing the rainfall impact at the traffic lane level that provides additional possibilities to apply traffic management measures on the traffic lane level instead of at the direction level only. Functional dependences and differences in capacity and speed on traffic lanes were found under the influence of different rainfall intensities. Reductions in free-flow speed depend on the rain category and traffic lanes and vary from 4.5% to 11.58%, while reductions in traffic lane capacity range from 2.46% to 12.97%. We demonstrate the importance of considering the impact of rainfall at the traffic lane level, which could be quality input data for defining appropriate traffic management measures to mitigate the negative impacts.
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Tanteliniaina, Mirindra Finaritra Rabezanahary, Jia Chen, Tanveer M. Adyel, and Jun Zhai. "Elevation Dependence of the Impact of Global Warming on Rainfall Variations in a Tropical Island." Water 12, no. 12 (December 21, 2020): 3582. http://dx.doi.org/10.3390/w12123582.
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Due to their vulnerability, understanding the impacts of global warming on rainfall is important for a tropical country and islands. This research aimed to assess the impact of global warming on rainfall in Madagascar, using the Mann-Kendall test, continuous wavelet transform, and polynomial regression. The result showed that the annual, seasonal maximum, and minimum temperature increased, while elevation amplified the increase of maximum temperature. Different trends in rainfall were found in the 22 regions of Madagascar but in general, the increasing trend in rainfall was prominent at a higher elevation than lower elevation. The annual rainfall decreased up to −5 mm per year for the regions located below 450 m of altitude while increased up to +5 mm per year above 500 m. We found that the wet becomes wetter with an important increase in rainfall in summer and the increase in temperature influenced the rainfall. The annual rainfall increased with temperature and elevation. However, if the increase in temperature was more than 0.03 °C per year, the annual rainfall increased regardless of elevation. The knowledge of the elevation dependence of the impact of warming on rainfall is important for water resources management and climate change adaptation strategies, especially for island nations and African countries.
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Tafoughalti, K., E. M. El Faleh, Y. Moujahid, and F. Ouargaga. "Climate Change Impact on Rainfall: How will Threaten Wheat Yield?" E3S Web of Conferences 37 (2018): 03001. http://dx.doi.org/10.1051/e3sconf/20183703001.
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Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.
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Allen, Theodore L., Scott Curtis, and Douglas W. Gamble. "The Midsummer Dry Spell’s Impact on Vegetation in Jamaica." Journal of Applied Meteorology and Climatology 49, no. 7 (July 1, 2010): 1590–95. http://dx.doi.org/10.1175/2010jamc2422.1.
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Abstract The annual rainfall pattern of the intra-Americas sea reveals a bimodal feature with a minimum during the midsummer known as the midsummer dry spell (MSD). A first attempt is made to examine the impact of the MSD on vegetation through a normalized difference vegetation index (NDVI) analysis in Jamaica. Tropical Rainfall Measuring Mission rainfall estimates and NDVI derived from the Terra Moderate Resolution Imaging Spectroradiometer highlight a consistent MSD feature in both rainfall and vegetative vigor. Spatial variation of this MSD NDVI response is evident throughout Jamaica, with the strongest relationship between the rainfall reduction and NDVI decline throughout the southern portions of Jamaica including the area of major domestic food production. In all years except 2005 there is a notable reduction from early-summer NDVI to midsummer NDVI in this agricultural region. However, the lagged vegetative response undergoes clear interannual variation and is affected by other forcings besides rainfall, such as brush fires and extreme wind.
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Valdez, L. D., G. J. Sibona, and C. A. Condat. "Impact of rainfall on Aedes aegypti populations." Ecological Modelling 385 (October 2018): 96–105. http://dx.doi.org/10.1016/j.ecolmodel.2018.07.003.
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Ngii, Edward. "Rainfall Infiltration Impact on Road Embankment Stability." Brilliant Engineering 4, no. 2 (April 4, 2023): 1–4. http://dx.doi.org/10.36937/ben.2023.4832.
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This study evaluates the stability of a widened road embankment slope by considering the effect of rain infiltration, which is often ignored in practical design. Rainfall infiltrates the soil and alters pore water pressure, reducing its shear strength and potentially causing slope failure. The Phi Index method is used to determine rain infiltration values, using rainfall data from four nearby rain stations over 10 years. The changes in pore water pressure resulting from rain infiltration are incorporated into the slope stability analysis by the limit equilibrium concept using the Spencer method. Back analysis is used to determine the soil shear strength parameters since the CPT test results provide a correlation with values within a certain range. Soil parameters resulting in a safety factor value close to 1.25 (critical condition) were considered representative field conditions. The analysis shows a decrease in the safety factor from 1.50 to 1.31 (12%). These findings emphasize the importance of accounting for rain infiltration in road embankment stability analyses, particularly in areas with high rainfall where the safety factor may fall below the minimum required by Indonesian geotechnical code. When an infiltration effect analysis is not conducted, the safety factor should be increased at least 12% from normal conditions.
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Dai, Qiang, Qiqi Yang, Jun Zhang, and Shuliang Zhang. "Impact of Gauge Representative Error on a Radar Rainfall Uncertainty Model." Journal of Applied Meteorology and Climatology 57, no. 12 (December 2018): 2769–87. http://dx.doi.org/10.1175/jamc-d-17-0272.1.
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AbstractIn modeling the radar rainfall uncertainty, rain gauge measurement is generally regarded as the areal “true” rainfall. However, the inconsistent scales between radar and gauge may introduce a new uncertainty (also known as gauge representative uncertainty), which is erroneously identified as radar rainfall uncertainty and therefore called pseudouncertainty. It is crucial to comprehend what percentage of the estimated radar rainfall uncertainty actually stems from such pseudouncertainty rather than radar rainfall itself. For this reason, based on a fully formulated radar rainfall uncertainty model, this study aims to explore how the gauge representative error affects the distribution, spatial dependence, and temporal dependence of hourly accumulated radar rainfall uncertainty, and consequently affects the produced radar rainfall uncertainty band. Three group scenarios that delineate various degrees of gauge representative errors were designed to configure and run the uncertainty model. In the setting of a long-term analysis (almost 7 years) of the Brue catchment in the United Kingdom, we found that the gauge representative error affected the simulation of the marginal distribution of radar rainfall error, and had a considerable effect on temporal dependence estimation of radar rainfall uncertainty. The spread of the rainfall uncertainty band decreased with the growth of the gauge density in a radar pixel. The scenario with the lowest representative error only had 78% uncertainty spread of the scenario that has the largest error. This indicated there was a large impact of the representative error on radar rainfall uncertainty models. It is hoped that more catchments with diverse climate and geographical conditions and more radar data with various spatial scales could be explored by the research community to further investigate this crucial issue.
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Valles, Jose, Gerald Corzo, and Dimitri Solomatine. "Impact of the Mean Areal Rainfall Calculation on a Modular Rainfall-Runoff Model." Journal of Marine Science and Engineering 8, no. 12 (December 2, 2020): 980. http://dx.doi.org/10.3390/jmse8120980.
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Hydrological models are based on the relationship between rainfall and discharge, which means that a poor representation of rainfall produces a poor streamflow result. Typically, a poor representation of rainfall input is produced by a gauge network that is not able to capture the rainfall event. The main objective of this study is to evaluate the impact of the mean areal rainfall on a modular rainfall-runoff model. These types of models are based on the divide-and-conquer approach and two specialized hydrological models for high and low regimes were built and then combined to form a committee of model that takes the strengths of both specialized models. The results show that the committee of models produces a reasonable reproduction of the observed flow for high and low flow regimes. Furthermore, a sensitivity analysis reveals that Ilopango and Jerusalem rainfall gauges are the most beneficial for discharge calculation since they appear in most of the rainfall subset that produces low Root Mean Square Error (RMSE) values. Conversely, the Puente Viejo and Panchimalco rainfall gauges are the least beneficial for the rainfall-runoff model since these gauges appear in most of the rainfall subset that produces high RMSE value.
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Sharma, Ashish, and Huei-Ping Huang. "Regional Climate Simulation for Arizona: Impact of Resolution on Precipitation." Advances in Meteorology 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/505726.
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This study performs regional climate simulations for Arizona, a region with complicated terrain. The dependence of simulated rainfall on model resolution is explore by climate downscaling experiments using the Weather Research and Forecasting model. The model’s horizontal resolution was refined from 12 to 6, then to 3 km. The total rainfall for winter and for different subdomains of Arizona is found to increase substantially with the refinement from 12 to 6 km grid. A further refinement to 3 km leads to a smaller change in rainfall, indicating numerical convergence at that scale. Comparisons with observations revealed that the 6 and 3 km runs produced excessive rainfall for winter while the 12 km simulations are closer to observation. This implies that the parameterization schemes for rainfall are not resolution independent, thus a refinement of resolution does not guarantee better results. It cautions against hastily pushing for increasingly higher resolution in practical downscaling simulations. An analysis of the simulated hourly rainfall shows that the 3 km runs produce significantly more extreme rainfall events than the 12 km runs. The 6 and 3 km runs also produced more complicated spatial patterns of seasonal rainfall and vertical velocity, reflecting the influence of fine-scale topography.
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Peng, Zheng, Ke Jinyan, Pan Wenbin, Zhan Xin, and Cai Yuanbin. "Effects of Low-Impact Development on Urban Rainfall Runoff under Different Rainfall Characteristics." Polish Journal of Environmental Studies 28, no. 2 (December 20, 2018): 771–83. http://dx.doi.org/10.15244/pjoes/85348.
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Villarini, G., and W. F. Krajewski. "Inference of Spatial Scaling Properties of Rainfall: Impact of Radar Rainfall Estimation Uncertainties." IEEE Geoscience and Remote Sensing Letters 6, no. 4 (October 2009): 812–15. http://dx.doi.org/10.1109/lgrs.2009.2025891.
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Cai, Wenju, Peter van Rensch, Tim Cowan, and Arnold Sullivan. "Asymmetry in ENSO Teleconnection with Regional Rainfall, Its Multidecadal Variability, and Impact." Journal of Climate 23, no. 18 (September 15, 2010): 4944–55. http://dx.doi.org/10.1175/2010jcli3501.1.
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Abstract An asymmetry, and its multidecadal variability, in a rainfall teleconnection with the El Niño–Southern Oscillation (ENSO) are described. Further, the breakdown of this relationship since 1980 is offered as a cause for a rainfall reduction in an ENSO-affected region, southeast Queensland (SEQ). There, austral summer rainfall has been declining since around the 1980s, but the associated process is not understood. It is demonstrated that the rainfall reduction is not simulated by the majority of current climate models forced with anthropogenic forcing factors. Examination shows that ENSO is a rainfall-generating mechanism for the region because of an asymmetry in its impact: the La Niña–rainfall relationship is statistically significant, as SEQ summer rainfall increases with La Niña amplitude; by contrast, the El Niño–induced rainfall reductions do not have a statistically significant relationship with El Niño amplitude. Since 1980, this asymmetry no longer operates, and La Niña events no longer induce a rainfall increase, leading to the observed SEQ rainfall reduction. A similar asymmetric rainfall teleconnection with ENSO Modoki exists and shares the same temporal evolutions. This breakdown is caused by an eastward shift in the Walker circulation and the convection center near Australia’s east coast, in association with a post-1980 positive phase of the interdecadal Pacific oscillation (IPO). Such a breakdown occurred before 1950, indicating that multidecadal variability alone could potentially be responsible for the recent SEQ rainfall decline. An aggregation of outputs from climate models to distill the impact of climate change suggests that the asymmetry and the breakdown may not be generated by climate change, although most models do not perform well in simulating the ENSO–rainfall teleconnection over the SEQ region.
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SINGH, BHIM, JITENDRA SINGH, PRERAK BHATNAGAR, and VK UPADHYAY. "Impact of rainfall variability on fruit production in Jhalawar district of Rajasthan." MAUSAM 65, no. 2 (April 1, 2014): 245–52. http://dx.doi.org/10.54302/mausam.v65i2.985.
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The objective of this study was to analyze the rainfall variability and trend, and examine vulnerability of fruits production to rainfall variability in Jhalawar district of Rajasthan. A time series data were used to carry out a comprehensive study of the effect of rainfall variability on fruit crops. It was observed that inter-annual and seasonal variabilities of rainfall were major cause of fluctuations in production of fruits in the study area. The district had 910 mm average rainfall with a standard deviation of 218 mm and coefficient of variation of 24 per cent. The annual rainfall as evident from analysis of data (1973-2010) showed negative trend (- 0.23 to - 17.41 mm/year) in the district. Productions of mandarin showed stronger correlations with the post-monsoon rainfall while those of mango, guava, lemon, mosambi, papaya, custard-apple and ber showed strong correlation with pre-monsoon and south-west monsoon rainfall.
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Oruc, Sertac. "Non-stationary Investigation of Extreme Rainfall." Civil Engineering Journal 7, no. 9 (September 1, 2021): 1620–33. http://dx.doi.org/10.28991/cej-2021-03091748.
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Natural or human-induced variability emerged from investigation of the traditional stationary assumption regarding extreme precipitation analyses. The frequency of extreme rainfall occurrence is expected to increase in the future and neglecting these changes will result in the underestimation of extreme events. However, applications of extremes accept the stationarity that assumes no change over time. Thus, non-stationarity of extreme precipitation of 5, 10, 15, and 30 minutes and 1-, 3-, 6-, and 24-hour data of 17 station in the Black Sea region were investigated in this study. Using one stationary and three non-stationary models for every station and storm duration, 136 stationary and 408 non-stationary models were constructed and compared. The results are presented as non-stationarity impact maps across the Black Sea Region to visualize the results, providing information about the spatial variability and the magnitude of impact as a percentage difference. Results revealed that nonstationary (NST) models outperformed the stationary model for almost all precipitation series at the 17 stations. The model in which time dependent location and scale parameter used (Model 1), performed better among the three different time variant non-stationary models (Model 1 as time variant location and scale parameters, Model 2 as time variant location parameter, and Model 3 as time variant scale parameter). Furthermore, non-stationary impacts exhibited site-specific behavior: Higher magnitudes of non-stationary impacts were observed for the eastern Black Sea region and the coastal line. Moreover, the non-stationary impacts were more explicit for the sub-hourly data, such as 5 minutes or 15 minutes, which can be one of the reasons for severe and frequent flooding events across the region. The results of this study indicate the importance of the selected covariate and the inclusion of it for the reliability of the model development. Spatial and temporal distribution of the nonstationary impacts and their magnitude also urges to further investigation of the impact on precipitation regime, intensification, severity. Doi: 10.28991/cej-2021-03091748 Full Text: PDF
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Vantas, Konstantinos, Epaminondas Sidiropoulos, and Athanasios Loukas. "Robustness Spatiotemporal Clustering and Trend Detection of Rainfall Erosivity Density in Greece." Water 11, no. 5 (May 20, 2019): 1050. http://dx.doi.org/10.3390/w11051050.
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Soil erosion is affected by rainfall, among other factors, and it is likely to increase in the future due to climate change impacts, resulting in higher rainfall intensities. This paper evaluates the impact of the missing values ratio on the computation of the rainfall erosivity factor, R, and erosivity density, ED. The paper also investigates the temporal trends and defines regions of Greece with a similar monthly distribution of ED using an unsupervised method. Preprocessed and free from noise and errors rainfall data from 108 stations across Greece were extracted from the Greek National Bank of Hydrological and Meteorological Information. The rainfall data were analyzed and erosive rainfalls were identified, their return period was determined using intensity–duration–frequency curves and R and ED values were computed. The impact of missing data in the computation of annual values of R and ED was investigated using a Monte Carlo simulation. The findings indicated that missing rainfall data resulted in a linear underestimation of R, while ED is more robust. The trends in ED timeseries were evaluated using the Kendall’s Tau test and their autocorrelation and partial autocorrelation were computed for a small subset of stations using criteria based on the quality of data. Furthermore, cluster analysis was applied to a larger subset of stations to define regions of Greece with similar monthly distribution of ED. The findings of this study indicate that: (a) ED should be preferred for the assessment of erosivity in Greece over the direct computation of R, (b) ED timeseries are found to be stationary for the majority of the selected stations, in contrast to reported precipitation trends for the same time period, (c) Greece is divided into three clusters/areas of stations with distinct monthly distributions of ED.
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Burke, Claire, and Peter Stott. "Impact of Anthropogenic Climate Change on the East Asian Summer Monsoon." Journal of Climate 30, no. 14 (July 2017): 5205–20. http://dx.doi.org/10.1175/jcli-d-16-0892.1.
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The East Asian summer monsoon (EASM) is important for bringing rainfall to large areas of China. Historically, variations in the EASM have had major impacts including flooding and drought. The authors present an analysis of the impact of anthropogenic climate change on EASM rainfall in eastern China using a newly updated attribution system. The results suggest that anthropogenic climate change has led to an overall decrease in total monsoon rainfall over the past 65 years and an increased number of dry days. However, the model also predicts that anthropogenic forcings have caused the most extreme heavy rainfall events to become shorter in duration and more intense. With the potential for future changes in aerosol and greenhouse gas emissions, historical trends in monsoon rainfall may not be indicative of future changes, although extreme rainfall is projected to increase over East Asia with continued warming in the region.
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Aldrees, A. "Climatic impact on Rainfall Analysis in Al-Madinah Munawwara Region." IOP Conference Series: Earth and Environmental Science 1026, no. 1 (May 1, 2022): 012032. http://dx.doi.org/10.1088/1755-1315/1026/1/012032.
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Abstract Long-term changes in temperature and weather patterns are referred to as climate change. Climate change and rainfall distribution are inextricably linked to arid and semi-arid regions. Saudi Arabia is entirely located in arid and semi-arid areas, and the arid climate that covers the majority of Saudi Arabia is typically characterized by large temporal and spatial variations in rainfall distribution. The availability of long-term rainfall depth records would be beneficial for studying the impact of climate change. This study aimed to assess the impact of climate change on rainfall analysis based on rainfall data generated by the HYFRAN-PLUS model during 1960–1990 and 1990–2020. Four rain-gauge stations near the Al-Madinah Munawwara region, namely Al Faqir, Umm Al Birak, Madinah Monawara, and Bir Al Mashi, were chosen for statistical analysis. The 1990–2020 rainfall data showed a significant climate change impact on the rainfall analysis at the Umm Al Birak station that was greater than that of the 1960–1990 data. The results of this study provide useful information for water resource planners and urban engineers to assess water availability and create appropriate storage systems considering climate change since 1960.
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Wu, Xiyuan, Xingxiu Yu, Yujiao Gao, and Guirong Wang. "Different Impacts of Rainfall Intensity on Surface Runoff and Sediment Loss between Huang-mian Soil and Brown Soil." Journal of Environmental Science and Management 20, no. 2 (December 31, 2017): 1–8. http://dx.doi.org/10.47125/jesam/2017_2/01.
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Huang-mian soil and brown soil are typical soils in Loess Plateau and Yimeng mountainous area, respectively. The differences of surface runoff and sediment loss between the two soils are important to special environmental protection management in two areas. In order to study the impacts of rainfall intensity on surface runoff and sediment from Huang-mian soil and brown soil, four simulated rainfalls were applied on fields with different soils on a laboratory scale. Huang-mian soil under 60×10-3 m hr-1 had the shortest runoff occurrence time, while brown soil under 30×10-3 m hr-1had the longest time; Huang-mian soil under 30×10-3 m hr-1 had the most sediments; Huang-mian soil has less loss of phosphorus (P) in concentration than brown soil, which explains why Loess Plateau has more soil and water loss but less eutrophication than the Yimeng mountainous area. Under the same rainfall intensity, Huang-mian soil had more runoff volume than brown soil; however, higher rainfall intensity decreased the difference. Increasing rainfall intensity had more impact on sediment content in brown soil than Huang-mian soil. It also had more impact on nitrate nitrogen (NO3--N) content in brown soil than ammonia nitrogen (NH4+-N) loss content in Huang-mian soil. Finally, suggestions were provided to reduce the harm of N and P loss in Huang-mian soil and brown soil regions.
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Bačinová, H., and P. Kovář. "Impact of overland flow on soil characteristics in Třebsín experimental plots." Soil and Water Research 12, No. 3 (June 28, 2017): 187–93. http://dx.doi.org/10.17221/133/2016-swr.
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This paper describes the continuation of simulated outcomes from the plots No. 4 and No. 5 with two different soils, using the KINFIL model to assess the runoff from extreme rainfall. The KINFIL model is a physically-based, parameter-distributed 3D model that has been applied to the Třebsín experimental station in the Czech Republic. This model was used for the first time in 2012 to simulate the impact of overland flow caused by natural or sprinkler-made intensive rains on four of the nine experimental plots. This measurement of a rain simulator producing a high-intensity rainfall involves also hydraulic conductivity, soil sorptivity, plot geometry and granulometric curves to be used for the present analysis. However, since 2012, the KINFIL model has been amended to provide a more effective comparison of the measured and computed results using the values of new parameters such as storage suction factor and field capacity on plot 4 and plot 5. The KINFIL model uses all input data mentioned above, and it produces the output data such as gross rainfall, effective rainfall, runoff discharge hydraulic depths, hydraulic velocities and shear velocities as well as shear stress values depending on the soil particle distribution. These processes are innovative, physically based, and both the measured and the computed results fit reliably.
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Tuyls, Damian Murla, Søren Thorndahl, and Michael R. Rasmussen. "Return period assessment of urban pluvial floods through modelling of rainfall–flood response." Journal of Hydroinformatics 20, no. 4 (April 13, 2018): 829–45. http://dx.doi.org/10.2166/hydro.2018.133.
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Abstract Intense rainfall in urban areas can often generate severe flood impacts. Consequently, it is crucial to design systems to minimize potential flood damages. Traditional, simple design of urban drainage systems assumes agreement between rainfall return period and its consequent flood return period; however, this does not always apply. Hydraulic infrastructures found in urban drainage systems can increase system heterogeneity and perturb the impact of severe rainfall response. In this study, a surface flood return period assessment was carried out at Lystrup (Denmark), which has received the impact of flooding in recent years. A 35 years' rainfall dataset together with a coupled 1D/2D surface and network model was used to analyse and assess flood return period response. Results show an ambiguous relation between rainfall and flood return periods indicating that linear rainfall–runoff relationships will, for the analysed case study, be insufficient for flood estimation. Simulation-based mapping of return periods for flood area and volume has been suggested, and moreover, a novel approach has been developed to map local flood response time and relate this to rainfall characteristics. This approach allows to carefully analyse rainfall impacts and flooding response for a correct flood return period assessment in urban areas.
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Johnson, K. A., J. C. Smithers, and R. E. Schulze. "A review of methods to account for impacts of non-stationary climate data on extreme rainfalls for design rainfall estimation in South Africa." Journal of the South African Institution of Civil Engineering 63, no. 3 (November 11, 2021): 1–7. http://dx.doi.org/10.17159/2309-8775/2021/v63n3a5.
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Frequency analysis of extreme rainfall and flood events are used to determine design rainfalls and design floods which are needed to design hydraulic structures such as dams, spillways and culverts. Standard methods for frequency analysis of extreme events are based on the assumption of a stationary climate. However, this assumption in rainfall and flood frequency analysis is being challenged with growing evidence of climate change. As a consequence of a changing climate, the frequency and magnitude of extreme rainfall events are reported to have increased in parts of South Africa, and these and other changes in extreme rainfall occurrences are expected to continue into the future. The possible non-stationarity in climate resulting in changes in rainfall may impact on the accuracy of the estimation of extreme rainfall quantities and design rainfall estimations. This may have significant consequences for the design of new hydraulic infrastructure, as well as for the rehabilitation of existing infrastructure. Hence, methods that account for non-stationary data, such as caused by climate change, need to be developed. This may be achieved by using data from downscaled global circulation models in order to identify non-stationary climate variables which affect rainfall, and which can then be incorporated into extreme value analysis of a non-stationary data series.
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Seprima, Melani, and Defrianto Defrianto. "PREDIKSI CURAH HUJAN DAN KELEMBABAN UDARA KOTA PEKANBARU MENGGUNAKAN METODE MONTE CARLO." Komunikasi Fisika Indonesia 17, no. 3 (November 30, 2020): 134. http://dx.doi.org/10.31258/jkfi.17.3.134-138.
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Weather prediction is important in our lives and can minimize the impact that will occur in the future. Rainfaal and humidity greatly affect the weather conditions in Indonesia. Accuracy in the prediction of rainfall and humidity is very important because it can be used in various interests. The data used are the monthly average data of rainfall and humidity in the city of Pekanbaru in 2014–2018 obtained from BMKG Pekanbaru, then the monthly average data will be processed using a MATLAB R2015a based program so that an average rainfall prediction simulation is obtained and air humidity in 2019–2023. MATLAB R2015a based program using the monte carlo method and has error value 0.0887913.
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Fajriani, Qonaah Rizqi, Khoirunnisa Ulya Nur Utari, and Ria Nurulita. "The Impact of Dam Reservoir on Flood Reduction (Case Study Logung Reservoir, Kudus, Central Java)." INERSIA lnformasi dan Ekspose Hasil Riset Teknik Sipil dan Arsitektur 18, no. 2 (December 31, 2022): 104–12. http://dx.doi.org/10.21831/inersia.v18i2.55409.
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The Indonesian government targeted building 65 reservoirs and dams in 2015-2022. The purpose is to maintain food security facing the long-term climate crisis, besides reducing the impact of a flood. Logung Reservoir is located on the Logung River, Kudus, Central Java. This earth-fill dam was built to solve the flood and drought problems in Kudus. However, the existence of the Logung Reservoir gives a risk to the downsteam area. The purpose of this research is to study flood reduction and the risk of overtopping, which can cause a dam break, and to calculate the Logung Reservoir spillway's performance in handling floods. This study is based on four main steps: the rainfal-runoff modelling, the extreme rainfall estimation, the hydrograph inflow of the dam estimation, and the evaluation of food reduction. The results of the 1000-year rainfall analysis and PMP for the Logung dam basin were 409 mm and 704 mm, respectively. Rainfall distribution is made using ABM, and effective rainfall is calculated by the SCS method. Land use analysis in the Logung dam watershed obtained a CN-II of 71.4 and a CN-III of 85.2. The rainfall-runoff transformation method used a unit hydrograph. The Nakayasu and Gama-I unit hydrographs show significant differences from the peak discharge, although not for the time base. The flood hydrograph design affects the reservoir performance. The reservoir flood routing results a dumping efficiency of 35% for the 1000-year and 21% for PMF. The 1000-year flood routing shows that there was no risk of overtopping. The highest water level on the PMF flood routing at +94.1. Several solutions can prevent overtopping by reducing inflow discharge through small dams upstream, increasing the green area, or modifying spillway structure.
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Eze, J. N., B. Z. Salihu, U. A. Gbanguba, M. Alfa, N. N. Ayanniyi, J. E. Ekaette, and B. O. Olaniyan. "Rainfall Variability and its Impact on Crop Production in Niger State, Nigeria." BADEGGI JOURNAL OF AGRICULTURAL RESEARCH AND ENVIRONMENT 3, no. 2 (June 2021): 46–55. http://dx.doi.org/10.35849/bjare202102015.
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The net potential effect of severe changes in rainfall pattern disrupts crop production leading to food insecurity, loss of jobs, and poverty. Crop production in Niger State is predominantly rain-fed, thus, exposing this major livelihood activity to the variability of rainfall. The study examined the impact of rainfall variability and its consequences on crop production. This is to integrate climate change adaptation options into agricultural activities. Strategies for climate change adaptation options in the study area have often been made without experimental foundations placed on the level of rainfall variability and its implications on crop production. To achieve this, a climatic index (CI) analysis of rainfall was employed to ascertain the level of rainfall extremes occurrences resulting from rainfall variability using standard deviation as a tool for rationalization. The study also used crop yield to test the relationship between the yield and rainfall characteristics for thirty years (1990-2019). Rainfall data and crop yield (soybean, maize, and sorghum) were collected. The data were analysed using statistical and climatic index analyses. The results show that there were various degrees of rainfall extremes that occurred (from mild to severe dry spell and mild to severe wet spell). Moreover, the regression analysis shows that F-values > p-values. Consequently, the occurrences of severe wet spells and mild to severe dry spells impacted negatively on crop production, which undermines food security. Based on the findings, recommendations were made to mainstream the adaptation options.
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Manz, Bastian Johann, Juan Pablo Rodríguez, Čedo Maksimović, and Neil McIntyre. "Impact of rainfall temporal resolution on urban water quality modelling performance and uncertainties." Water Science and Technology 68, no. 1 (July 1, 2013): 68–75. http://dx.doi.org/10.2166/wst.2013.224.
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A key control on the response of an urban drainage model is how well the observed rainfall records represent the real rainfall variability. Particularly in urban catchments with fast response flow regimes, the selection of temporal resolution in rainfall data collection is critical. Furthermore, the impact of the rainfall variability on the model response is amplified for water quality estimates, as uncertainty in rainfall intensity affects both the rainfall-runoff and pollutant wash-off sub-models, thus compounding uncertainties. A modelling study was designed to investigate the impact of altering rainfall temporal resolution on the magnitude and behaviour of uncertainties associated with the hydrological modelling compared with water quality modelling. The case study was an 85-ha combined sewer sub-catchment in Bogotá (Colombia). Water quality estimates showed greater sensitivity to the inter-event variability in rainfall hyetograph characteristics than to changes in the rainfall input temporal resolution. Overall, uncertainties from the water quality model were two- to five-fold those of the hydrological model. However, owing to the intrinsic scarcity of observations in urban water quality modelling, total model output uncertainties, especially from the water quality model, were too large to make recommendations for particular model structures or parameter values with respect to rainfall temporal resolution.
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Cai, Wenju, Peter van Rensch, Tim Cowan, and Harry H. Hendon. "Teleconnection Pathways of ENSO and the IOD and the Mechanisms for Impacts on Australian Rainfall." Journal of Climate 24, no. 15 (August 1, 2011): 3910–23. http://dx.doi.org/10.1175/2011jcli4129.1.
Full textAbstract:
Abstract Impacts of El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) on Australian rainfall are diagnosed from the perspective of tropical and extratropical teleconnections triggered by tropical sea surface temperature (SST) variations. The tropical teleconnection is understood as the equatorially trapped, deep baroclinic response to the diabatic (convective) heating anomalies induced by the tropical SST anomalies. These diabatic heating anomalies also excite equivalent barotropic Rossby wave trains that propagate into the extratropics. The main direct tropical teleconnection during ENSO is the Southern Oscillation (SO), whose impact on Australian rainfall is argued to be mainly confined to near-tropical portions of eastern Australia. Rainfall is suppressed during El Niño because near-tropical eastern Australia directly experiences subsidence and higher surface pressure associated with the western pole of the SO. Impacts on extratropical Australian rainfall during El Niño are argued to stem primarily from the Rossby wave trains forced by convective variations in the Indian Ocean, for which the IOD is a primary source of variability. These equivalent-barotropic Rossby wave trains emanating from the Indian Ocean induce changes to the midlatitude westerlies across southern Australia, thereby affecting rainfall through changes in mean-state baroclinicity, west–east steering, and possibly orographic effects. Although the IOD does not mature until austral spring, its impact on Australian rainfall during winter is also ascribed to this mechanism. Because ENSO is largely unrelated to the IOD during austral winter, there is limited impact of ENSO on rainfall across southern latitudes of Australia in winter. A strong impact of ENSO on southern Australia rainfall in spring is ascribed to the strong covariation of ENSO and the IOD in this season. Implications of this pathway from the tropical Indian Ocean for impacts of both the IOD and ENSO on southern Australian climate are discussed with regard to the ability to make seasonal climate predictions and with regard to the role of trends in tropical SST for driving trends in Australian climate.
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Alfahmi, Furqon, Rizaldi Boer, Rahmat Hidayat, Perdinan, and Ardhasena Sopaheluwakan. "The Impact of Concave Coastline on Rainfall Offshore Distribution over Indonesian Maritime Continent." Scientific World Journal 2019 (January 1, 2019): 1–11. http://dx.doi.org/10.1155/2019/6839012.
Full textAbstract:
Indonesian Maritime Continent has the second longest coastline in the world, but the characteristics of offshore rainfall and its relation to coastline type are not clearly understood. As a region with eighty percent being an ocean, knowledge of offshore rainfall is important to support activity over oceans. This study investigates the climatology of offshore rainfall based on TRMM 3B42 composite during 1998-2015 and its dynamical atmosphere which induces high rainfall intensity using WRF-ARW. The result shows that concave coastline drives the increasing rainfall over ocean with Cenderawasih Bay (widest concave coastline) having the highest rainfall offshore intensity (16.5 mm per day) over Indonesian Maritime Continent. Monthly peak offshore rainfall over concave coastline is related to direction of concave coastline and peak of diurnal cycle influenced by the shifting of low level convergence. Concave coastline facing the north has peak during northwesterly monsoonal flow (March), while concave coastline facing the east has peak during easterly monsoonal flow (July). Low level convergence zone shifts from inland during daytime to ocean during nighttime. Due to shape of concave coastline, land breeze strengthens low level convergence and supports merging rainfall over ocean during nighttime. Rainfall propagating from the area around inland to ocean is approximately 5.4 m/s over Cenderawasih Bay and 4.1 m/s over Tolo Bay. Merger rainfall and low level convergence are playing role in increasing offshore rainfall over concave coastline.
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Othman Alia, Rawshan, Zhao Chunjua, Zhou Yihona, Liu Ping, Arien Heryansyaha, and Nadeem Nawaz. "Impact of climatic change on water resources in Huia river basin, China." International Journal of Engineering & Technology 7, no. 4 (September 16, 2018): 2225. http://dx.doi.org/10.14419/ijet.v7i4.15788.
Full textAbstract:
Research on the impact of climate change on water resources has attracted the attention of academician and policy makers. This paper tends to analyze the impact of changes in air temperature and rainfall factors on the amount of water resources in the Huai River Basin from 1980 to 2014. Air temperature and rainfall data were collected from six meteorological stations. Hydrological and water resources evaluation data were collected from the Bengbu Hydrological Station in the Huai River Basin. Research findings revealed an increasing trend of average annual air temperature, with the highest increase of 0.293oC recorded at Bengbu in Anhui Province. The western part of the study area has shown a rising rainfall while the eastern part (the middle reaches of the Huai River) witnessed a declining rainfall. The rainfall in the Huai River Basin was significantly influenced by the natural fluctuations as the average rainfall in the study area was in a vaguely declining trend. This resulted in gradual decrease in the quantity of the Basin’s water resources due to decreasing rainfall and rising air temperature. Regression and sensitivity analyses were employed to develop a mathematical model between water resources quantity and changes in air temperature and rainfall. Based on regression analysis findings, changes in rainfall have a much bigger impact on its water resources quantity than changes in its air temperature.